Salient object detection (SOD) is an important task in computer vision that aims to identify
visually conspicuous regions in images. RGB-Thermal SOD combines two spectra to …

Federated cross learning has shown impressive performance in medical image
segmentation. However, it encounters the catastrophic forgetting issue caused by data …

The active contour model (ACM) plays a paramount part in grasping visual properties of
images and exacting targets of interest. It is overwhelming hardship for traditional ACMs to …

The phenomenon of adversarial examples has been revealed in variant scenarios. Recent
studies show that well-designed adversarial defense strategies can improve the robustness …

Speckle noise and intensity inhomogeneity are always challenging issues in the area of
image segmentation, especially when both difficulties appear simultaneously …

In recent years, graph-cut algorithms have been considered in image segmentation due to
their quality and computational load. Among these algorithms, radius-based function kernel …

Neural architecture search (NAS) has emerged as one successful technique to find robust
deep neural network (DNN) architectures. However, most existing robustness evaluations in …

Document image binarization plays a vital role in the document image analysis system;
however, it remains challenging due to various degradations. In this paper, we propose an …

Excellent performance has been achieved on semi-supervised medical image
segmentation, but existing algorithms perform relatively poorly for objects with variable …

Even though the level set method is driving progress in image segmentation, its
performance is still affected adversely in the presence of severe intensity inhomogeneity and …